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Record W4323668929 · doi:10.3390/genes14030673

Selection and Validation of Reference Genes for Gene Expression Studies in an Equine Adipose-Derived Mesenchymal Stem Cell Differentiation Model by Proteome Analysis and Reverse-Transcriptase Quantitative Real-Time PCR

2023· article· en· W4323668929 on OpenAlexaff
Angela Riveroll, Sabrina Skyba-Lewin, K. Devon Lynn, Glady’s Mubyeyi, Ahmad Abd‐El‐Aziz, Frederick S.B. Kibenge, Molly Kibenge, Alejandro Cohen, Blanca Esparza-Gonsalez, Laurie A. McDuffee, William Montelpare

Bibliographic record

VenueGenes · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsDalhousie UniversityUniversity of Prince Edward Island
Fundersnot available
KeywordsMesenchymal stem cellAdipose tissueGene expressionBiologyRUNX2Molecular biologyGeneProteomeMessenger RNAStem cellReal-time polymerase chain reactionGene expression profilingCell biologyBioinformaticsGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Adipose-derived stem cells (ADSCs) are used in tissue regeneration therapies. The objective of this study is to identify stable reference genes (RGs) for use in gene expression studies in a characterized equine adipose-derived mesenchymal stem cell (EADMSC) differentiation model. ADSCs were differentiated into adipocytes (ADs) or osteoblasts (OBs), and the proteomes from these cells were analyzed by liquid chromatography tandem mass spectrometry. Proteins that were stably expressed in all three cells types were identified, and the mRNA expression stabilities for their corresponding genes were validated by RT-qPCR. PPP6R1, CCDC97, and then either ACTB or EPHA2 demonstrated the most stable mRNA levels. Normalizing target gene Cq data with at least three of these RGs simultaneously, as per MIQE guidelines (PPP6R1 and CCDC97 with either ACTB or EPHA2), resulted in congruent conclusions. FABP5 expression was increased in ADs (5.99 and 8.00 fold, p = 0.00002 and p = 0.0003) and in OBs (5.18 and 5.91 fold, p = 0.0011 and p = 0.0023) relative to ADSCs. RUNX2 expression was slightly higher in ADs relative to ADSCs (1.97 and 2.65 fold, p = 0.04 and p = 0.01), but not in OBs (0.9 and 1.03 fold, p = 0.58 and p = 0.91).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.333
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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